Selected work

Publication / BNAIC–BeNeLearn 2023

Assessing aggressive driving behaviour.

A study of attention-based online action detection, hybrid model design, and interpretable cues in driving video.

Authors
J. Aechtner, A. Wilbik & M. Popa
Published
Springer · 2025
DOI
10.1007/978-3-031-74650-5_4
A car driving on a European road at blue hour
AI-generated image

The paper

Detecting actions as they unfold.

We investigated aggressive driving behaviour on the METEOR dataset using two online action-detection models, OadTR and Colar. The study evaluates their respective strengths and examines how class frequency in the training data relates to classification accuracy.

We also developed a hybrid architecture that combines categorical exemplars with future-frame prediction. To make its output more interpretable, we traced agent paths across space and time to identify salient cues behind individual predictions.